【埃森哲Accenture】2025人工智能规模化应用领跑者指南行业领导者经验启示

Thefront-runners’guidetoscalingAI

Lessonsfromindustryleaders

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accenture

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Authors

SenthilRamani

GlobalLeadforData&AI,

Accenture

LanGuan

ChiefAIOfficer,Accenture

Thefront-runners’guidetoscalingAI:Lessonsfromindustryleaders

PhilippeRoussiere

GlobalLeadfor

InnovationandAI,

AccentureResearch

2

>Thefront-runners’guidetoscalingAI:Lessonsfromindustryleaders3

Abouttheresearch

Wesurveyed2,000C-suiteanddata-science

executives,wholead1,998oftheworld’slargest

companies(revenuesgreaterthan$1billion,whichare

headquarteredin15countries(Australia,Brazil,Canada,China,Germany,France,India,Italy,Japan,SaudiArabia,Singapore,Spain,UnitedArabEmirates,UnitedKingdomandUnitedStates)andoperateinnineindustries

(banking,insurance,energy,consumergoodsand

services,lifesciences,utilities,retail,publicservicesandcommunicationsandmedia).Thesurvey,fieldedfrom

JunetoJuly2024,aimedtoshedlightonhowcompaniesdevelopanddeployAImodelstocreatefinancialand

non-financialvalue.Thesurveycoveredtopicssuch

asorganizations’dataandAIstrategy,dataandAI

architecture,budgetsfor—andinvestmentsin—strategicbets,talentstrategy,ecosystemstrategy,responsibleAI,AI-relatedchallengesandAIadoptionrates.

Toidentifythemostimportantstrategicbets(see“Get

strategic,”above),wealsointerviewednumerousC-suiteexpertswithinandoutsideAccenture.Inaddition,we

deployedmachinelearningtoidentifyboththekey

capabilitiesassociatedwithscalingstrategicbetsand

companies’progressindevelopingthosecapabilities.

TheresearchwasfurtherenrichedwithinsightsfromourextensiveexperiencehelpingclientsscaleAIsolutions.Bydrawingonthesediverseinputs,ourfindingsthus

capturebothstrategicperspectivesonAIandreal-worldexecutionchallenges.

Forthepurposesofthisreport,“scalingAI”refersto

theprocessofexpandingAIimplementationacrossan

enterprisetoachievebroader,moreimpactfuloutcomes.ScalingincludesintegratingAIintodiversebusiness

processesandworkflows;ensuringwidespreadadoptionacrossassetsandemployees;seamlesslyintegrating

AIwithexistingsystems;drivinginnovationtogaina

competitiveedgeinthemarket;andotherwiseimprovingkeyperformancemetrics.“GenerativeAI”describes

anumbrellatermforartificialintelligencethatcan

producebrand-newoutput—suchastext,images,videos,audioandcode.

Executivesummary

ThougheverybusinessmaywantanAI-powerededge,manycompaniesarestillstrugglingtoadvancebeyondtheirinitial

AIexperiments.Abigreasonforthis,ourresearchalsoshows,islowdata“readiness”—whichariseswhenalltypesofdata,

especiallyunstructureddata,arenotusedtothemax.

Encouragingly,mostbusinessleadersrecognizethischallenge.Forexample,70%ofthecompanieswesurveyedacknowledgedtheneedforastrongdatafoundationwhentryingtoscaleAI.

Data,ofcourse,isn’ttheonlyobstacletoenterprisereinvention

withgenAI.OutdatedITsystems,aswellasworkers’lackofaccessto,respectively,genAItools,comprehensivetrainingandclear

guidancefromleadershiparesignificantbarriers,too.

Atthesametime,ourresearchrevealedthatasmallminorityofcompanies(“front-runners”)arealreadyachievingconsiderablesuccessatreinventingtheirenterpriseswithgenAI.These

companiesconsistentlygetoneveryimportantthingright:They combinewhatwecall“tablestakes”investmentsingenAIwith“strategicbets”(seesidebar,“Getstrategic”).

Front-runners,forexample,useagenticAIintheirtablestakesto

boostefficiency.Andintheirstrategicbets,theydeployagenticAItoradicallyreinventtheirorganizationalprocessesandworkflows.

70%ofthecompanies

wesurveyed

acknowledgedthe

needforastrongdata

foundationwhen

tryingtoscaleAI.

Forbusinesses,securingasustainedadvantageovercompetitorswaslongtheHolyGrail—acoveted,yetelusiveprize.Today,

however,generativeartificialintelligenceandotherformsofAI

haveflippedthescript,bringingthepreviouslyunattainablewithinreach.That’swhytheworld’slargestcompaniesareinvesting

heavilyindataandAI.

ButreinventingtheenterprisewithgenerativeAI(genAI)isn’t

simplyamatterofdeployingafewchatbots.ReinventionisaboutbuildingadvancedAIcapabilitieslike“agenticarchitecture,”

networksofAIagentsthatgobeyondautomatingroutinetaskstoorchestratingentirebusinessworkflows.

Endowedwithsophisticatedreasoning,AIagentscollaborate

autonomouslytoimprovequality,productivityandcost-efficiencyatscale.Agenticarchitectureisspreadingfast:one-thirdofthe

companieswesurveyedforthisreport(See‘’Abouttheresearch’’onpage38)arealreadyusingAIagentstostrengthentheir

innovationcapabilities.

ReinventionthusrequiresintegratingAIdeeplyintothecoreofacompany’sstrategy.Todothis,businesses,undertheproactiveleadershipoftheirCEOandboard,mustgobeyondsurface-levelapplicationsofAIandprioritizestructuralandstrategicchangesthatunlockAI’sfullpotential.

>Thefront-runners’guidetoscalingAI:Lessonsfromindustryleaders4

Getstrategic

“Strategicbets”aresignificant,long-term

investmentsingenAIthatfocusonthe

coreofacompany’svaluechain(suchas

underwritingandclaimsforaninsurer,

assetmanagementforautilityand,R&D

foralifesciencesfirm)andthatalsooffer

averylargepayoff.Strategicbetsaimto

maximizethepotentialofgenAItodrive

transformative,industry-specific,process-

levelefficiencies,aswellasexceptional

productivity,innovationandrevenuegrowth.

“Tablestakes”aretheopposite:foundational

investmentsthatdrivebroadAIadoptionwithinanorganizationandvalidatethetechnology’s

abilitytohandlespecificusescases(suchas

customer-supportcentersthatseamlesslymovebetweentextandvoiceinteractions).While

tablestakesofferonlyincrementalvalue,theyarestillessentialproofpointsofAImaturity.

Soevenastheyfocusonafewstrategicbetstodriveenterprisereinvention,companies

shouldcontinuewithtablestakesaswell.

Touncoverthemostimportantstrategicbets

ineachofthenineindustrieswestudied,we

solicitedtheviewsofAccentureexpertswhohaveadvisedclientson2,000recentgenAIprojects.

WealsointerviewedexternalAIexpertsatvariouslargecompaniesaroundtheworld.Through

theseconsultations,wearrivedat105strategicbets—orjustover11perindustry,onaverage.

(Someindustrieshadmorestrategicbetsthanothers;see“Appendix1:The105strategicbets”and“Appendix2:Researchmethodology.”).

Later,oursurveyof2,000executives*frommanyoftheworld’slargestcompaniesrevealedthe

extenttowhichtheseorganizationshaveadoptedgenAIbyscalingtheirrespective,industry-

focused,strategicbets.Companiesintheutilitiesindustry,say,wereaskedabouttheirexperiencewith10utilities-focusedstrategicbets.One

question,forexample,assessedcompanies’levelofgenAIadoptionaroundtheirstrategicbeton“augmentedassetmanagement”.Companies

couldthenansweralongaspectrum,from“noadoption”to“fullscaling”acrosstheenterprise.

Wefoundthat34%ofsurveyed

companieshavescaledatleastone

strategicbet.SuchcompaniesalsospendsignificantlymoreoncloudandAI

(devoting51%oftheirtechnologybudgetstotheseareas)thandocompaniesthat

havenotscaledanystrategicbets(45%oftheirrespectivetechbudgets).

5

>Thefront-runners’guidetoscalingAI:LessonsfromindustryleadersThesurveycovered2,000executives,from1,998companies.

Thestatedmarginoferroris+/-2.2percentagepointsatthe95%confidenceintervalmidpoint.

Companiesthatscalestrategicbetsareusually

delightedwiththeirfinancialperformanceaswell.Forinstance,comparedtocompetitorsthathave

notdoneso,companiesthathavescaledatleastonestrategicbetarenearlythreetimesmorelikelyto

havetheirreturnoninvestment(ROI)fromgenAIsurpasstheirforecasts.

Butregardlessofwhethertheyhavealot,oralittle,worktodobeforetheyscalemorestrategicbets,allthecompanieswesurveyedexpectbigthingsfromreinventionwithgenAI.Onaverage,theseorganizationsexpecta13%

increaseinproductivity,a12%increaseinrevenuegrowth,an11%improvementincustomerexperience,andan11%decreaseincostswithin18monthsof

deployingandscalinggenAIacrosstheirenterprise.

Drawingonourempiricalresearchandextensiveclientwork,thisreport

exploresthedistinguishingtraitsofAIreinvention-readycompanies,which

remainpoorlyunderstood.Inthefollowingpages,weidentifytheessential

dataandAIcapabilitiesthatfront-runnerspossess—anddescribesfive

imperativesthatallowfront-runnerstoscaletheirstrategicbetseffectively(foradditionalanalysisofthefiveimperatives,seetheAccenturereports,“

Making

ReinventionRealwithGenAI

”and“

ReinventionintheageofgenerativeAI

”):

1.Leadwithvalue

2.Reinventtalentandwaysofworking

3.BuildanAI-enabled,securedigitalcore

4.ClosethegaponresponsibleAI

5.Drivecontinuousreinvention

Asthisreportmakesclear,artificialintelligencehasalreadymovedpastits

familiarroleasapowerfultoolforboostingefficiency.Whenusedtoitsfull

potential,AIisnowsomethingfargreater:anunstoppableforceforenterprisereinvention,allowingcompaniestogrowfasterandinnovatebetterthanrivals.

>Thefront-runners’guidetoscalingAI:Lessonsfromindustryleaders6

Whatmakesacompanyreinvention-readyforAI?

>Thefront-runners’guidetoscalingAI:Lessonsfromindustryleaders7

>Thefront-runners’guidetoscalingAI:Lessonsfromindustryleaders8

In2022,weidentifiedasmallgroupofcompaniesthat

wereleadersinfoundationaldataandAIcapabilities

(seeAppendix2).1Today,these“AIreinvention-ready”

companiesstillexcelatthebasics.Butthey’realsohoningtheirgenAIcapabilitiestogreateffect.

AIreinvention-readycompanies,ourresearchalsoshows,representonlyafractionoftheworld’slargestbusinesses(just15%oftheorganizationswestudied).Inourschema,thesecond-mostadvancedgrouparecompaniesthat

areprogressingwithAI(43%ofcompanies),followedbycompaniesthataremerelyexperimentingwithAI(42%).

Here’showwearrivedatthesethreegroups.Wecreatedanindextomeasureandcategorizecompaniesbasedontheirmaturityindevelopinganddeployingthecapabilitiesthat

aremostcriticaltoscalingstrategicbetsingenAI.

Wediscoveredthatthemostadvancedgroup,AI

reinvention-readycompanies,haveachievedhighlevels

ofmaturity(seetheirlarge“webs”inFigure1),inboththefoundationalcapabilitiesandinwhatwecallthe“new

dataandAIessentialcapabilities”forgenAI.Thelatterarecomprisedoflargelanguagemodeloperations(LLMOps)maturity,datamanagementandgovernance(DM&G)–

newessentials,datasource,foundationmodelspractice,andtalentpractice.(SeeAppendix2forthefulllistof

foundationalandnewcapabilities.)

Figure1:Webofprogress

Reinvention-readycompanieshavemorematuredataandAIcapabilities

capabilities

experimentingwithAI

F1

progressingwithAI

F1

AIreinvention-ready

F1

F1:Data&AIstrategy

F2:AI

platformmaturity

75%

50%

25%

F3:DM&Gmaturity

&AIessentialcapabilities

N1

N1

:LLMOpsMaturity

N2:DM&G

new

essentials

N1

75%

50%

25%

N5

N4N3

N5

N4N3

N3:Datasource

Foundational

F5

F3

F4

F2

F5

F3

F4

F2

F5

F3

F4

F2

F5:RAImaturity

F4:Talent

maturity

NewData

N1

N5

N4N3

N2

N5:Talentpractice

N2

N2

N4:Foundationmodelspractice

Source:AccentureResearch.Thelargertheareaoftheweb,themorematurethecapabilities.

Figure2:AppreciatetheEight

Only8%oforganizationsareAIreinvention-readyfront-runners

Meanwhile,companiesthatareprogressingwithAIdemonstrate

8%

7%

43%

42%

intermediatelevelsofmaturityinthosecapabilities(medium-sizedwebsinFigure1).Andcompaniesthatareexperimentinghavecomparativelylow

front-runners

fast-followers

levelsofmaturity(smallwebs).

AI

reinvention-ready

AIreinvention-readycompanieshave,inshort,developedstrongdigitalcores,whichareessentialforscalingAIanddata-driveninitiatives,

ensuringdataaccessibility,computingperformanceandsecurity.2

Withoutastrongdigitalcore,businessesaremorelikelytounderperformandstruggletoadapttorapidlychangingenvironments.

That’sthemacroview.Themicroview,however,showsthatnotall

progressingwithAI

reinvention-readycompaniesareequallyproficientatscalingstrategicbetsingenAI.Infact,wefoundthatsomeofthesecompanies(“front-runners”)havealreadyscaledmultiplestrategicbets,whileothers(“fastfollowers”)haveyettoscaleanystrategicbets(Figure2).

experimentingwithAI

Source:AccentureResearch.

>Thefront-runners’guidetoscalingAI:Lessonsfromindustryleaders9

Breakingaway—how

front-runnersarescalingAI

>Thefront-runners’guidetoscalingAI:Lessonsfromindustryleaders10

>Thefront-runners’guidetoscalingAI:Lessonsfromindustryleaders11

Whatdistinguishesfront-runnersfromfast-followersistheirrelativeaptitudeatdeployingandscalingstrategicbets.

Indeed,front-runnersnotonlyplacemorestrategicbetsbutalsoscalethematasignificantlyhigherratethanothercompaniesdo.AsFigure3illustrates,front-runnershave,onaverage,alreadyscaled34%of

thestrategicbets(orthreetofourbets)thataremostrelevanttotheirindustry;another40%offront-runners’strategicbetsareintheearlystagesofscaling.

Fast-followers,ontheotherhand,havenotyetfullyscaledany

strategicbets,withonly33%intheearlystagesofscaling.The

numbersforcompaniesthatareprogressingwithAI(8%ofstrategic

betsscaled,32%intheearlystages)andforcompaniesthatareonlyexperimentingwithAI(5%and28%,respectively)similarlyunderscorethegaptheyneedtoclose.

Figure3:Scaleforsuccess

front-runnershavescaled34%oftheirstrategicbets,onaverage

front-runners

fast-followers

progressingwithAI

experimentingwithAI

60%

30%

0%

60%

30%

0%

60%

30%

0%

60%

30%

0%

40%

23%

3%

34%

51%

16%

0%

33%

44%

8%

16%

32%

45%

22%

28%

5%

not

plannedearlyscaled

stages

planned

Source:AccentureResearch.

>Thefront-runners’guidetoscalingAI:Lessonsfromindustryleaders12

Sowhydofront-runnersexcelatscalingstrategic

bets?Afterall,morefast-followers(89%)thanfront-runners(81%)havealreadydevelopedthefiveAI

foundationalcapabilitiesreferencedinFigure1.

Tounderstandwhy,lookfirsttothenewdataandAI

essentialcapabilitiesforgenAI.Here,front-runners

haveaclearedge:Wefoundthat28%offront-runnershavedevelopedallfiveofthesecapabilities,comparedtoonly19%offast-followers.

Theedgeisalsoevidentwhenfront-runnersare

comparedtoothercompanies.AsFigure4shows,97%offront-runnershavedevelopedthreeormoreofthenewdataandAIessentialcapabilitiesfor

genAI,comparedtojust5%ofcompaniesthatareexperimentingwithAI(Figure4).

Figure4:ThenewdataandAIessentialcapabilitiesforgenAI

Nearlyallfront-runnershaveadoptedthreeormoreofthese

front-runners

fast-followers

progressingwithAI

experimentingwithAI

97%offront-runnershaveachievedatleast3outof5advancedmaturitylevelofNewData&AIEssential

capabilities

Only5%ofexperimentingwithAImanagetoachieve3outof5advancedmaturitylevel

ofNewData&AIEssentialcapabilities

#ofNewDataandAI

1outof5

2outof5

3outof5

4outof5

5outof5

0outof5

EssentialCapabilities

achievingadvancedlevel

Source:AccentureResearch.

Considerotherdistinguishingtraitsoffront-runners.ThesecompaniesaremorelikelytohavestrongCEOandboard

sponsorshipfortheirAIinvestmentsthanfast-followers

(19%vs.5%,respectively,ofsurveyedcompanies).Front-runnersarealsomorelikelythanfast-followers(59%vs.

36%)tohavefullyintegratedtheircoreAIstrategy,criticalprocesses,andtechnologycapabilitiesintoacohesive

framework.Morebroadly,front-runnersarethreetimes

morelikelythanothercompaniestohaveachievedahighlevelofmaturitywiththeirAIplatforms.

Front-runnersprioritizepeople-centeredchange,too:

They’refourtimesmorelikelythanfast-followerstofocusonculturalissuesthatimpedechange;threetimesmorelikelytoemphasizetalentalignmentandtransparent

communication;threetimesmorelikelytouseinsightsfrombehavioralsciencetocontinuouslymonitorthe

impactofAI-drivenchange;andtwotimesmorelikelytoofferstructuredtrainingprogramsforemployees.

Tobesure,front-runnersdon’thaveanedgeateverythingAI-related.Fast-followers,forexample,areparticularly

strongattalentdevelopment;96%offast-followersfocusoncultivatingspecializedAItalent(suchasAIengineers),comparedto88%offront-runners.

Fastfollowersareneverthelessheldbackinthisarea,

ourresearchalsorevealed,becausetheymostlylack

acentralizedoperatingmodel—suchasa“centerof

excellence”thatservesasthefocalpointforacompany’sAIstrategy,developmentanddeployment.Forexample,only16%offast-followershaveacentralizedoperating

model,while57%offront-runnersdo.

Anotherimportantdifferentiatorforfront-runnersisthat

they’remorelikelytobeskilledatusingandcontinuouslyimprovingautonomousAIagentsthataretailoredto

industryneeds.Forinstance,65%offront-runnersare

skilledinthisarea,comparedto50%offast-followers.

Front-runners,likewise,aremoreadeptthanfast-followersatdefiningthebusinessvaluefromtheirAIusecases.

Whenitcomestodata,fast-followersdopossesscertainadvantages.Forexample,96%areverystrongindata

governance,comparedto83%offront-runners.Dittofordataplatforms(98%vs.90%,respectively).

Butinmanyotherdata-relatedpractices,fast-followers

lagfarbehind.Forexample,17%offront-runnersuse

“retrieval-augmentedgeneration”toenhancetheirLLMs,whileonly1%offast-followersdo.Similarly,front-runners

aremuchmorelikelythanfast-followerstodothingslikeuse“knowledgegraphs”tostructureandcontextualizedata(26%v.3%)andmanagedataeffectivelyoverthe

entiredatalifecycle(22%vs.6%).

Whenitcomestoleveragingdiversedatasources,front-

runnersholdaclearedgeaswell.Forinstance,they’re

morelikelythanfast-followerstoheavilyusezero-party

data(44%vs.4%),second-partydata(30%vs.7%),third-partydata(25%vs.8%)andsyntheticdata(35%vs.6%).Fast-followers,incontrast,areonlyslightlymorelikely

thanfront-runnerstoheavilyusefirst-partydata(60%vs.67%)andtacitknowledge(72%vs.68%).3

Beforegoingallinonstrategicbets,Telstra,Australia’s

leadingtelecommunicationscompany,wiselysetabout

simplifyingandmodernizingitsdataecosystem.This

involvesconsolidatingover40platformsintoasmall,

integrated,datafoundation.Oncetherearchitectingis

completed,TelstrawillbefarbetterplacedtorapidlyscaleitsgenAIcapabilities.

>Thefront-runners’guidetoscalingAI:Lessonsfromindustryleaders13

TheAIrace—whichindustriesaretakingthelead

>Thefront-runners’guidetoscalingAI:Lessonsfromindustryleaders14

Ourresearchalsorevealedtheindustriesthathave

madethemostprogressscalingstrategicbets.Figure

5illustrateshowfront-runnersaremostprevalent

inthelifesciences(accountingfor12%ofsurveyed

>Thefront-runners’guidetoscalingAI:Lessonsfromindustryleaders

companiesinthatindustry)andleastcommoninretail(2%,respectively).

Figure5:TheAIlife

front-runnersaremostprevalentinthelife-sciencesindustry

fast-followers

progressingwithAI

experimentingwithAI

12%

6%

4%

4%

6%

12%

9%

2%

10%

39%

29%

45%

39%

42%

32%

47%

63%

49%

37%

55%

43%

49%

45%

48%

39%

30%

39%

LifeSciences

Insurance

Utilities

C&M

Banking

Energy

CG&S

PublicServices

Retail

8%

7%

42%

44%

Average

15

Industriesorderedbytheshareoffront-runnerswithineachindustry.C&M=communicationsandmedia;CG&S=consumergoodsandservices.Source:AccentureResearch.

front-runners

12%

10%

9%

9%

8%

7%

5%

5%

2%

Figure6showsthethreemost-scaledstrategic

betsbyindustry.Inlifesciences,forexample,16%

ofcompanieshavescaledtheirstrategicbeton

acceleratingtimetoapproval;14%havescaledtheirstrategicbetonacceleratingtimetoclinic;and13%havescaledtheirstrategicbetonmaximizingthe

valuepropositionofmedicines.

>Thefront-runners’guidetoscalingAI:Lessonsfromindustryleaders

Figure6:Threecheers

Thethreemostscaledstrategicbetsbyindustry

Industry#1#2#3

LifeSciences

Acceleratetimetoapproval

16%

Acceleratetimetoclinic

14%

Maximizehealthandeconomicoutcomes

13%

Insurance

Fraud

detection

23%

Call

assistance

13%

Claimsintake

12%

Utilities

Workforceoperationsoptimization

11%

Generation

forecasting

10%

Customer

pricingstrategy

9%

Communications

Self-healing

automatednetwork

13%

Agentco-pilot

12%

Fieldengineer

technicalassistant

11%

Media

Chatbotstohelpwith

contentretrieval

andcompliancequeries

18%

Frauddetectionandprevention

14%

Dynamicadcampaignsandplacement

10%

Banking

Fraudmanagement

29%

Cardsandpayments

29%

Knowyourcustomer

6%

Energy

Healthandsafety

14%

Automaticanalysisandwork-ordergeneration

13%

Tradingpredictions

11%

CG&S

Real-timecustomer

9%

Agilebrandexperiencedesignanddevelopment

7%

Hyper-personalizedconsum-erprofilingandsegmentation

7%

PublicServices

Knowledgemanagementforreportingoranalysis

27%

ITmodernizationandcodegeneration

16%

Backlogreductionsincriticalservices

16%

Retail

Automatedworkforcescheduling

6%

Channel-specific

customersegmentation

6%

Persona-baseddigital

marketingcontentcreation

5%

Source:AccentureResearch.Industriesareorderedbytheshareoffront-runnerswithineachindustry,withlifescienceshavingthegreatestshareandretailthelowestshare.Communicationsandmediaareseparatedinthistable,butnotelsewhere,